A quick and dirty visualization you could do this way. I did the example based on these crops:
count1.tif (1.1 MB)
count2.tif (1.1 MB)
Take your images with the overlay. Transfer them to the ROI Manager (if the points are already selections you can skip this step:
Image > Overlay > To ROI Manager
Select the detection’s in the ROI Manager then create masks:
Edit > Selection > Create Mask
Please rename the mask image then otherwise the image will be overwritten by another create masks operation: Image > Rename…
The detection’s are now binary masks (8-bit, 0 and 255).
You can dilate them so they are more visible.
Process > Binary > Dilate
Mask1.tif (352.3 KB)
Mask2.tif (352.3 KB)
Then you can show the different detection’s on top of the original image.
First convert the RGB original image into 8-bit:
Image > Type > 8-bit
Then merge the different images as channels:
Image > Color > Merge Channels…
Add the original image as grey, one marker image as green the other as red.
You can then see the individual detection’s next to each other.
Composite.tif (1.0 MB)
One can improve on this. But from this quick visualization you can already see that it is not so easy as a simple overlap. Essentially to get a better result is to write a script that takes the locations and computes the locations that are close enough to be selecting the same object. Maybe someone here solved something like this already. Its not rocket science but needs a bit of development.
You can maybe consider to use the cell counter (https://imagej.nih.gov/ij/plugins/cell-counter.html) or the MTB cell counter (https://mitobo.informatik.uni-halle.de/index.php/Applications/MTBCellCounter)
this allows to save and load marker and visualize them with different colors.